"Understanding Persistent Memory and Context Management" matching MCP servers:

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

A configurable MCP server that intelligently routes natural language queries to the appropriate microservice endpoint based on user-defined service configurations.

A simple MCP server that can enable MCP clients to query Bluesky instances.

Enables AI agents to safely inspect a PortalV4 project's real structure, database schema, and Git status, while enforcing backend architecture rules, automating API documentation, and generating test templates without modifying repositories.

An MCP server that enables interaction with Google's My Business Account Management API, allowing users to perform account management operations through natural language interactions.

An MCP server that enables management of Google Play games via the Google Games Management API, allowing automated interactions for game resets, hiding/unhiding data, and player management through natural language commands.

A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

A proxy server that bridges AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools, enabling seamless interaction without custom integration code.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

Official MCP (Model Context Protocol) server for Iron.xyz API, designed to work with Claude Desktop, Cursor IDE and other MCP compatible clients.

Webhook management and testing tools for AI agents. Provides tools for sending, validating, generating, and debugging webhooks.

An MCP server for Tern that enables the generation, verification, and management of webhook handlers across over 16 platforms and various frameworks. It provides tools to create verified endpoints, debug signature failures, and manage failed event replays via dead letter queues.

Enables AI assistants to interact with Fastly's CDN API through the Model Context Protocol, allowing secure management of CDN services, caching, security settings, and performance monitoring without exposing API keys.

Enables AI agents to lint API artifacts (OpenAPI, AsyncAPI, Arazzo) and manage rulesets conversationally via the Model Context Protocol.

A generic MCP (Model Context Protocol) server that bridges any GraphQL API to Claude Code. It introspects your GraphQL schema and exposes each query and mutation as an individual tool, letting Claude interact with your API directly.